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Automated driving systems are in need of accurate localization, i.e., achieving accuracies below 0.1 m at confidence levels above 95%. Although during the last decade numerous localization techniques have been proposed, a common methodology to validate their accuracies in relation to a ground-truth dataset is missing so far. This work aims at closing this gap by evaluating four different methods for validating localization accuracies of a vehicle’s position trajectory to different ground truths: (1) a static driving-path, (2) the lane-centerline of a high-definition (HD) map with validated accuracy, (3) localized vehicle body overlaps of the lane-boundaries of a HD map, and (4) longitudinal accuracy at stop points. The methods are evaluated using two localization test datasets, one acquired by an automated vehicle following a static driving path, being additionally equipped with roof-mounted localization systems, and a second dataset acquired from manually-driven connected vehicles. Results show the broad applicability of the approach for evaluating localization accuracy and reveal the pros and cons of the different methods and ground truths. Results also show the feasibility of achieving localization accuracies below 0.1 m at confidence levels up to 99.9% for high-quality localization systems, while at the same time demonstrate that such accuracies are still challenging to achieve.
Karl Rehrl; Simon Gröchenig. Evaluating Localization Accuracy of Automated Driving Systems. Sensors 2021, 21, 5855 .
AMA StyleKarl Rehrl, Simon Gröchenig. Evaluating Localization Accuracy of Automated Driving Systems. Sensors. 2021; 21 (17):5855.
Chicago/Turabian StyleKarl Rehrl; Simon Gröchenig. 2021. "Evaluating Localization Accuracy of Automated Driving Systems." Sensors 21, no. 17: 5855.
Travel time reliability (TTR) indices have gained considerable attention for evaluating the quality of traffic infrastructure. Whereas TTR measures have been widely explored using data from stationary sensors with high penetration rates, there is a lack of research on calculating TTR from mobile sensors such as probe vehicle data (PVD) which is characterized by low penetration rates. PVD is a relevant data source for analyzing non-highway routes, as they are often not sufficiently covered by stationary sensors. The paper presents a methodology for analyzing TTR on (sub-)urban and rural routes with sparse PVD as the only data source that could be used by road authorities or traffic planners. Especially in the case of sparse data, spatial and temporal aggregations could have great impact, which are investigated on two levels: first, the width of time of day (TOD) intervals and second, the length of road segments. The spatial and temporal aggregation effects on travel time index (TTI) as prominent TTR measure are analyzed within an exemplary case study including three different routes. TTI patterns are calculated from data of one year grouped by different days-of-week (DOW) groups and the TOD. The case study shows that using well-chosen temporal and spatial aggregations, even with sparse PVD, an in-depth analysis of traffic patterns is possible.
Markus Steinmaßl; Stefan Kranzinger; Karl Rehrl. Analyzing Travel Time Reliability from Sparse Probe Vehicle Data: A Case Study on the Effects of Spatial and Temporal Aggregation. Transportation Research Record: Journal of the Transportation Research Board 2021, 1 .
AMA StyleMarkus Steinmaßl, Stefan Kranzinger, Karl Rehrl. Analyzing Travel Time Reliability from Sparse Probe Vehicle Data: A Case Study on the Effects of Spatial and Temporal Aggregation. Transportation Research Record: Journal of the Transportation Research Board. 2021; ():1.
Chicago/Turabian StyleMarkus Steinmaßl; Stefan Kranzinger; Karl Rehrl. 2021. "Analyzing Travel Time Reliability from Sparse Probe Vehicle Data: A Case Study on the Effects of Spatial and Temporal Aggregation." Transportation Research Record: Journal of the Transportation Research Board , no. : 1.
In the context of intelligent transport systems, dynamic route planning is an eagerly researched topic. While the research community during the last decade has focused on performance and scalability of dynamic route planning algorithms, the question concerning route qualities has been widely neglected. The current work contributes to this question by proposing a methodology to assess the quality of arbitrary routes based on seven spatio‐temporal route quality metrics (five spatial and two temporal ones). The methodology is evaluated by calculating quality metrics for 45 routes being derived from three dynamic route planning systems for three selected origin–destination pairs during one day. For objectively assessing route qualities, the approach matches the route planning results to a reference digital road network and uses reference travel times for calculating quality metrics. A spatio‐temporal cross‐evaluation illustrates different quality aspects in the context of both quality dimensions and demonstrates the usefulness of the proposed approach.
Karl Rehrl; Stefan Kranzinger; Simon Gröchenig. Which quality is a route? A methodology for assessing route quality using spatio‐temporal metrics. Transactions in GIS 2020, 25, 869 -896.
AMA StyleKarl Rehrl, Stefan Kranzinger, Simon Gröchenig. Which quality is a route? A methodology for assessing route quality using spatio‐temporal metrics. Transactions in GIS. 2020; 25 (2):869-896.
Chicago/Turabian StyleKarl Rehrl; Stefan Kranzinger; Simon Gröchenig. 2020. "Which quality is a route? A methodology for assessing route quality using spatio‐temporal metrics." Transactions in GIS 25, no. 2: 869-896.
Trajectory data mining is a lively research field in the domain of spatio-temporal data mining. Trajectory pattern mining comprises a set of specific pattern mining methods, which are applied as consecutive steps on a trajectory with the goal to extract and classify re-occurring spatio-temporal patterns. Despite the common nature and frequent usage of such methods by the GIScience community, a methodological approach is missing so far, especially when it comes to the use of machine learning-based classification methods. The current work closes this gap by proposing and evaluating a machine learning-based 3-steps trajectory data mining methodology using the detection and classification of stop points in vehicle trajectories as example. The work describes in detail the applied methodologies with respect to the three mining steps ‘stop detection’, ‘feature extraction’ and ‘classification in traffic-relevant and non-traffic-relevant stops’ and evaluates six machine learning-based classification algorithms using a real-world dataset of 15,498 vehicle trajectories with 5,899 detected stops (thereof 2,032 manually classified). Due to its exemplary nature, the presented methodology is suited to act as blueprint for similar trajectory data mining problems.
Karl Rehrl; Simon Gröchenig; Stefan Kranzinger. Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories. International Journal of Geographical Information Science 2020, 34, 1953 -1979.
AMA StyleKarl Rehrl, Simon Gröchenig, Stefan Kranzinger. Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories. International Journal of Geographical Information Science. 2020; 34 (10):1953-1979.
Chicago/Turabian StyleKarl Rehrl; Simon Gröchenig; Stefan Kranzinger. 2020. "Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories." International Journal of Geographical Information Science 34, no. 10: 1953-1979.
Richard Brunauer; Nina Schmitzberger; Karl Rehrl. Recognizing Spatio-Temporal Traffic Patterns at Intersections Using Self-Organizing Maps. Proceedings of the 11th ACM SIGSPATIAL International Workshop on Computational Transportation Science 2018, 43 -52.
AMA StyleRichard Brunauer, Nina Schmitzberger, Karl Rehrl. Recognizing Spatio-Temporal Traffic Patterns at Intersections Using Self-Organizing Maps. Proceedings of the 11th ACM SIGSPATIAL International Workshop on Computational Transportation Science. 2018; ():43-52.
Chicago/Turabian StyleRichard Brunauer; Nina Schmitzberger; Karl Rehrl. 2018. "Recognizing Spatio-Temporal Traffic Patterns at Intersections Using Self-Organizing Maps." Proceedings of the 11th ACM SIGSPATIAL International Workshop on Computational Transportation Science , no. : 43-52.
From April to November 2017, the non-profit research organisation Salzburg Research conducted the “Digibus© 2017” trial, the first trial of a self-driving shuttle on a public road in Austria. The shuttle from the French company Navya Tech has been tested on a 1.4-km long track in the village of Koppl, which is situated approximately ten kilometres east from the City of Salzburg. The trial in Koppl was one of the first trials worldwide on public roads with mixed traffic in a rural area. The focus of this trial was on the real-world evaluation of a self-driving shuttle for bridging the first/last mile in public transport. From April to November 2017, 240 test drives with 874 passengers covering 341 test kilometres have been conducted. Results show that the technology is ready for testing, but there is still a long way to go for driverless operation, especially in mixed traffic scenarios. The work describes the trial setting, the test route, the process of deploying the shuttle, experiences collected during the trial as well as results from a passenger survey. The accompanying passenger survey with 294 participants revealed high acceptance and a good feeling of safety.
Karl Rehrl; Cornelia Zankl. Digibus©: results from the first self-driving shuttle trial on a public road in Austria. European Transport Research Review 2018, 10, 51 .
AMA StyleKarl Rehrl, Cornelia Zankl. Digibus©: results from the first self-driving shuttle trial on a public road in Austria. European Transport Research Review. 2018; 10 (2):51.
Chicago/Turabian StyleKarl Rehrl; Cornelia Zankl. 2018. "Digibus©: results from the first self-driving shuttle trial on a public road in Austria." European Transport Research Review 10, no. 2: 51.
Map matching, i.e. matching a moving entity’s position trajectory to an underlying transport network, is a crucial functionality of many location-based services. During the last decade, numerous map-matching algorithms have been proposed, tackling challenging aspects like sparse trajectory data or online matching. This work describes GraphiumMM, an open-source map-matching implementation combining and optimizing geometrical and topological matching concepts from previous works. The implementation aims at highly accurate and performant map matching in online and offline mode taking trajectories with average sampling intervals between 1 and 120 s as input. For evaluating its runtime performance and matching quality, results are compared to results from the open-source map-matcher Barefoot. Results indicate better matching quality and runtime performance especially for sampling intervals from 1 to 15 s in offline and online mode.
Karl Rehrl; Simon Gröchenig; Michael Wimmer. Optimization and Evaluation of a High-Performance Open-Source Map-Matching Implementation. Lecture Notes in Geoinformation and Cartography 2018, 251 -270.
AMA StyleKarl Rehrl, Simon Gröchenig, Michael Wimmer. Optimization and Evaluation of a High-Performance Open-Source Map-Matching Implementation. Lecture Notes in Geoinformation and Cartography. 2018; ():251-270.
Chicago/Turabian StyleKarl Rehrl; Simon Gröchenig; Michael Wimmer. 2018. "Optimization and Evaluation of a High-Performance Open-Source Map-Matching Implementation." Lecture Notes in Geoinformation and Cartography , no. : 251-270.
Network-wide dynamic link flow estimation is one of the challenging questions in transportation research. Most of the previous approaches rely on static or dynamic OD matrices. The proposed data-driven approach tackles the problem of link flow estimation as a local network propagation problem between cross-section measurement sites. Distinct propagation rules consider time-dependent travel speeds, turning fractions at intersections and vehicle gain-loss ratios between links. The rules are derived from recorded vehicle paths originating from a probe vehicle data (PVD) system including data from thousands of vehicles from several different fleets. The proposed approach introduces a algorithm with dedicated propagation rules and measures for evaluating propagation quality. Our approach is evaluated using Austria's nation-wide road network (including freeways, urban and rural roads) with approximately 224,443 links and 16,566 intersections as well as traffic count data from 664 cross-section measurement sites. Results show the general applicability of the approach, but also reveal several challenging situations, which have to be treated with suitable propagation strategies.
Richard Brunauer; Stefan Henneberger; Karl Rehrl. Network-wide link flow estimation through probe vehicle data supported count propagation. 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) 2017, 1 -8.
AMA StyleRichard Brunauer, Stefan Henneberger, Karl Rehrl. Network-wide link flow estimation through probe vehicle data supported count propagation. 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). 2017; ():1-8.
Chicago/Turabian StyleRichard Brunauer; Stefan Henneberger; Karl Rehrl. 2017. "Network-wide link flow estimation through probe vehicle data supported count propagation." 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) , no. : 1-8.
Location referencing systems (LRS) are a crucial requisite for referencing traffic information to a road network. In the past, several methods and standards for static or dynamic location referencing have been proposed. All of them support machine-interpretable location references but only some of them include human-interpretable concepts. If included, these references are based on pre-defined locations (e.g. as location catalogue) and often miss meaningful interlinking with road network models (e.g. locations being simply mapped to geographic coordinates). In a parallel research strand, ontological concepts for structuring road networks based on human conceptualizations of space have been proposed. So far, both methods have not been integrated. The current work closes this gap and proposes a generation process for meaningful location references on top of road networks based on qualitative spatial concepts. A prototypical implementation using OWL, Neo4J graph database and a standardized nationwide road network graph shows the practical applicability of the approach. Results indicate that the proposed approach is able to bridge the gap between existing road network models and human conceptualizations on multiple levels of abstraction.
Karl Rehrl; Richard Brunauer; Simon Gröchenig; Eva Lugstein. Generation of Meaningful Location References for Referencing Traffic Information to Road Networks Using Qualitative Spatial Concepts. Lecture Notes in Geoinformation and Cartography 2016, 173 -191.
AMA StyleKarl Rehrl, Richard Brunauer, Simon Gröchenig, Eva Lugstein. Generation of Meaningful Location References for Referencing Traffic Information to Road Networks Using Qualitative Spatial Concepts. Lecture Notes in Geoinformation and Cartography. 2016; ():173-191.
Chicago/Turabian StyleKarl Rehrl; Richard Brunauer; Simon Gröchenig; Eva Lugstein. 2016. "Generation of Meaningful Location References for Referencing Traffic Information to Road Networks Using Qualitative Spatial Concepts." Lecture Notes in Geoinformation and Cartography , no. : 173-191.
Cornelia Schneider; Sebastian Zutz; Karl Rehrl; Richard Brunauer; Simon Gröchenig. Evaluating GPS sampling rates for pedestrian assistant systems. Journal of Location Based Services 2016, 10, 1 -28.
AMA StyleCornelia Schneider, Sebastian Zutz, Karl Rehrl, Richard Brunauer, Simon Gröchenig. Evaluating GPS sampling rates for pedestrian assistant systems. Journal of Location Based Services. 2016; 10 (3):1-28.
Chicago/Turabian StyleCornelia Schneider; Sebastian Zutz; Karl Rehrl; Richard Brunauer; Simon Gröchenig. 2016. "Evaluating GPS sampling rates for pedestrian assistant systems." Journal of Location Based Services 10, no. 3: 1-28.
Mobilität als System betrachtet ist vielschichtig, hoch dynamisch und komplex. Aufgrund von unterschiedlichen Einflussfaktoren ist das System einem ständigen Wandel unterzogen und nur schwer zu verstehen und zu kontrollieren. Der folgende Artikel beschreibt, wie Fragestellungen im Bereich der Mobilität mit Hilfe von Big Data untersucht und besser verstanden werden können. Hierbei geht es einerseits um den Zugang zu und die Nutzbarmachung von geeigneten Datenquellen, die das System „Mobilität“ beschreiben, andererseits aber auch darum, wie die Daten aufbereitet werden müssen, um als Entscheidungsgrundlagen für aktuelle und zukünftige Fragestellungen geeignet zu sein. Erstes wird zeigen, dass vor allem die Integration von unterschiedlichsten Datenquellen neue, bisher nicht betrachtete Blickwinkel auf das Mobilitätsgeschehen zulässt. Zweites geht der Frage nach, wie aus der Vielzahl von heute sowie zukünftig verfügbaren Datenquellen Mobilitätsinformationen extrahiert werden können, die in Folge von unterschiedlichen Stakeholdern unterschiedlich genutzt werden. Für Mobilitätsdienstleister, Mobilitätsentscheidungsträger und Mobilitätsforscher bedeutet Big Data vor allem ein Umdenken von modellbasierten zu (mehr) datengetriebenen Methoden zur Systembeschreibung. Für Mobilitätsteilnehmer bewegt sich Big Data zwischen der optimierten und einfacheren Erfüllung von Mobilitätsbedürfnissen und der totalen Überwachung. Der Beitrag zeigt anhand von konkreten Beispielen, dass Big Data in der Mobilität nicht das Ziel sondern die logische Konsequenz der fortschreitenden Digitalisierung ist. Aus heutiger Sicht scheinen Digitalisierung und Datenintegration allen Stakeholdern einen Vorteil zu verschaffen, wodurch sich ein Nutzen sowohl für den Einzelnen aber auch für die Gesellschaft ergibt.
Richard Brunauer; Karl Rehrl. Big Data in der Mobilität – FCD Modellregion Salzburg. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016, 235 -267.
AMA StyleRichard Brunauer, Karl Rehrl. Big Data in der Mobilität – FCD Modellregion Salzburg. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2016; ():235-267.
Chicago/Turabian StyleRichard Brunauer; Karl Rehrl. 2016. "Big Data in der Mobilität – FCD Modellregion Salzburg." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 235-267.
Over the last decade, volunteered geographic information (VGI) has become established as one of the most relevant geographic data sources in terms of worldwide coverage, representation of local knowledge and open data policies. Beside the data itself, data about community activity provides valuable insights into the mapping progress which can be useful for estimating data quality, understanding the activity of VGI communities or predicting future developments. This work proposes a conceptual as well as technical framework for structuring and analyzing mapping activity building on the concepts of activity theory. Taking OpenStreetMap as an example, the work outlines the necessary steps for converting database changes into user- and feature-centered operations and higher-level actions acting as a universal scheme for arbitrary spatio-temporal analyses of mapping activities. Different examples from continent to region and city-scale analyses demonstrate the practicability of the approach. Instead of focusing on the interpretation of specific analysis results, the work contributes on a meta-level by addressing several conceptual and technical questions with respect to the overall process of analyzing VGI community activity.
Karl Rehrl; Simon Gröchenig. A Framework for Data-Centric Analysis of Mapping Activity in the Context of Volunteered Geographic Information. ISPRS International Journal of Geo-Information 2016, 5, 37 .
AMA StyleKarl Rehrl, Simon Gröchenig. A Framework for Data-Centric Analysis of Mapping Activity in the Context of Volunteered Geographic Information. ISPRS International Journal of Geo-Information. 2016; 5 (3):37.
Chicago/Turabian StyleKarl Rehrl; Simon Gröchenig. 2016. "A Framework for Data-Centric Analysis of Mapping Activity in the Context of Volunteered Geographic Information." ISPRS International Journal of Geo-Information 5, no. 3: 37.
This work reports on results from a field trial regarding the collection of floating car data with smartphones in Austria. The field trial has been conducted within Austria’s National Floating Car Data Testbed pursuing the goal to test different aspects of floating car data technology for traffic data collection, traffic state estimation and traffic prediction. The test bed collects, processes and analyses FCD from several thousand vehicles. The field trial for smartphone-based data collection has been conducted within the Federal State of Salzburg covering 1500 kilometres of major road network. Between the launch of the Android-based smartphone application in March 2014 and the end of the field trial in February 2015, the application has been downloaded by more than 2100 users. One year after launch the app is still installed on 650 devices and attracts around 15 users daily. The work gives insights into the application’s concepts and discusses app usage statistics, usage patterns and user feedback in the context of community-driven traffic data collection. On the one hand, results from the field trial confirm that community-driven traffic data collection is still not a phenomenon of the masses due to various challenges discussed throughout the work. On the other hand, results contribute to a deeper understanding of community-driven data collection in the traffic domain and help to learn for future trials.
Karl Rehrl; Richard Brunauer; Simon Gröchenig. Collecting floating car data with smartphones: results from a field trial in Austria. Journal of Location Based Services 2016, 10, 16 -30.
AMA StyleKarl Rehrl, Richard Brunauer, Simon Gröchenig. Collecting floating car data with smartphones: results from a field trial in Austria. Journal of Location Based Services. 2016; 10 (1):16-30.
Chicago/Turabian StyleKarl Rehrl; Richard Brunauer; Simon Gröchenig. 2016. "Collecting floating car data with smartphones: results from a field trial in Austria." Journal of Location Based Services 10, no. 1: 16-30.
Changes are immanent to digital geographic vector datasets. While the majority of changes nowadays are quantitatively detectable by the use of geographic information systems their classification and impact assessment on a qualitative level with respect to specific data usage scenarios is often neglected. To close this gap, this work proposes a classification approach consisting of three parts: (1) a taxonomy for classifying quantitatively detectable edits in digital feature datasets (e.g. attribute or geometry changes), (2) a taxonomy for classifying edits into qualitative and therefore meaningful change types (e.g. feature revision or identity change) and (3) a mapping scheme providing the link from quantitative to qualitative classifications. In the context of a case study with OpenStreetMap history data the proposed classification approach is used to automatically detect and classify feature changes with respect to two feature types, namely streets and buildings, leading to a refined mapping scheme for two selected data usage scenarios, namely vehicle routing and map rendering. Results show the applicability of the approach, especially for assessing the impact of feature changes on different data usage scenarios, and provide a useful foundation for any change detection task in the context of geographic vector datasets.
Karl Rehrl; Richard Brunauer; Simon Gröchenig. Towards a Qualitative Assessment of Changes in Geographic Vector Datasets. Lecture Notes in Geoinformation and Cartography 2015, 181 -197.
AMA StyleKarl Rehrl, Richard Brunauer, Simon Gröchenig. Towards a Qualitative Assessment of Changes in Geographic Vector Datasets. Lecture Notes in Geoinformation and Cartography. 2015; ():181-197.
Chicago/Turabian StyleKarl Rehrl; Richard Brunauer; Simon Gröchenig. 2015. "Towards a Qualitative Assessment of Changes in Geographic Vector Datasets." Lecture Notes in Geoinformation and Cartography , no. : 181-197.
Richard Brunauer; Karl Rehrl. Deriving driver-centric travel information by mining delay patterns from single GPS trajectories. Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science 2014, 25 -30.
AMA StyleRichard Brunauer, Karl Rehrl. Deriving driver-centric travel information by mining delay patterns from single GPS trajectories. Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science. 2014; ():25-30.
Chicago/Turabian StyleRichard Brunauer; Karl Rehrl. 2014. "Deriving driver-centric travel information by mining delay patterns from single GPS trajectories." Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science , no. : 25-30.
Volunteered geographic information (VGI) data-sets are characterised by heterogeneity due to influences from technical, social, environmental or economic factors. As a result, mapping progress does neither follow a spatially nor a temporally equal distribution, and thus can be hardly measured or predicted. Positively stated, heterogeneity leads to interesting VGI data-sets revealing regional peculiarities such as diverse community activities. This work proposes an approach for identifying regionally and temporally different developments with respect to mapping progress. Regional mapping progress is measured with a modified version of a previously proposed model for classifying activity stages, which has been used as foundation for a massive spatial and temporal analysis of the worldwide OpenStreetMap contributions between the years 2006 and 2013. It also allows the evaluation of rural and unpopulated areas. Results reveal that regional mapping progress heavily depends on a number of distinct influences such as geographical or legal borders, data imports, unexpected events or diverse community developments. The work highlights regions with distinct results by revealing individual mapping stories.
Simon Gröchenig; Richard Brunauer; Karl Rehrl. Digging into the history of VGI data-sets: results from a worldwide study on OpenStreetMap mapping activity. Journal of Location Based Services 2014, 8, 198 -210.
AMA StyleSimon Gröchenig, Richard Brunauer, Karl Rehrl. Digging into the history of VGI data-sets: results from a worldwide study on OpenStreetMap mapping activity. Journal of Location Based Services. 2014; 8 (3):198-210.
Chicago/Turabian StyleSimon Gröchenig; Richard Brunauer; Karl Rehrl. 2014. "Digging into the history of VGI data-sets: results from a worldwide study on OpenStreetMap mapping activity." Journal of Location Based Services 8, no. 3: 198-210.
Due to the dynamic nature and heterogeneity of Volunteered Geographic Information (VGI) datasets a crucial question isu concerned with geographic data quality. Among others, one of the main quality categories addresses data completeness. Most of the previous work tackles this question by comparing VGI datasets to external reference datasets. Although such comparisons give valuable insights, questions about the quality of the external dataset and syntactic as well as semantic differences arise. This work proposes a novel approach for internal estimation of regional data completeness of VGI datasets by analyzing the changes in community activity over time periods. It builds on empirical evidence that completeness of selected feature classes in distinct geographical regions may only be achieved when community activity in the selected region runs through a well-defined sequence of activity stages beginning at the start stage, continuing with some years of growth and finally reaching saturation. For the retrospective calculation of activity stages, the annual shares of new features in combination with empirically founded heuristic rules for stage transitions are used. As a proof-of-concept the approach is applied to the OpenStreetMap History dataset by analyzing activity stages for 12 representative metropolitan areas. Results give empirical evidence that reaching the saturation stage is an adequate indication for a certain degree of data completeness in the selected regions. Results also show similarities and differences of community activity in the different cities, revealing that community activity stages follow similar rules but with significant temporal variances.
Simon Gröchenig; Richard Brunauer; Karl Rehrl. Estimating Completeness of VGI Datasets by Analyzing Community Activity Over Time Periods. Lecture Notes in Geoinformation and Cartography 2014, 3 -18.
AMA StyleSimon Gröchenig, Richard Brunauer, Karl Rehrl. Estimating Completeness of VGI Datasets by Analyzing Community Activity Over Time Periods. Lecture Notes in Geoinformation and Cartography. 2014; ():3-18.
Chicago/Turabian StyleSimon Gröchenig; Richard Brunauer; Karl Rehrl. 2014. "Estimating Completeness of VGI Datasets by Analyzing Community Activity Over Time Periods." Lecture Notes in Geoinformation and Cartography , no. : 3-18.
Karl Rehrl; Elisabeth Häusler; Sven Leitinger; Daniel Bell. Pedestrian navigation with augmented reality, voice and digital map: final results from anin situfield study assessing performance and user experience. Journal of Location Based Services 2014, 8, 75 -96.
AMA StyleKarl Rehrl, Elisabeth Häusler, Sven Leitinger, Daniel Bell. Pedestrian navigation with augmented reality, voice and digital map: final results from anin situfield study assessing performance and user experience. Journal of Location Based Services. 2014; 8 (2):75-96.
Chicago/Turabian StyleKarl Rehrl; Elisabeth Häusler; Sven Leitinger; Daniel Bell. 2014. "Pedestrian navigation with augmented reality, voice and digital map: final results from anin situfield study assessing performance and user experience." Journal of Location Based Services 8, no. 2: 75-96.
This paper presents a summary of the Action and Interaction in Volunteered Geographic Information international workshop which was held as a one day pre-conference workshop to the 16th Annual Association of Geographic Information Laboratories in Europe conference in Leuven, Belgium in May 2013. This paper summarises the important outcomes of workshop presentations and key discussion statements from participant contributions to an open-floor discussion on the most pertinent issues in Volunteered Geographic Information (VGI) research. Participants engaged this discussion focused on what are the most likely problems which could form the basis for a research agenda in VGI composed of both short- and long-term research objectives. While the development of a VGI research agenda will require the involvement of the broadest possible spectrum of disciplines, this paper is, none-the-less, an important first step on this journey.
Peter Mooney; Karl Rehrl; Hartwig Hochmair. Action and interaction in volunteered geographic information: a workshop review. Journal of Location Based Services 2013, 7, 291 -311.
AMA StylePeter Mooney, Karl Rehrl, Hartwig Hochmair. Action and interaction in volunteered geographic information: a workshop review. Journal of Location Based Services. 2013; 7 (4):291-311.
Chicago/Turabian StylePeter Mooney; Karl Rehrl; Hartwig Hochmair. 2013. "Action and interaction in volunteered geographic information: a workshop review." Journal of Location Based Services 7, no. 4: 291-311.
Travel modes are one of the crucial pieces of information to characterize one's travel behavior. In recent years several approaches of mode detection from GPS data have been proposed. The approach presented in this paper uses machine learning to evaluate a set of GPS-based features for their ability to recognize the common modes walk, bicycle, car, bus, and train. The proposed features describe motion characteristics from GPS-trajectories by relative frequencies. Compared to previous work the proposed feature set leads to higher average recognition rates around 92% without relying on additional GIS or real-time information. The evaluation compares detection rates from multilayer perceptrons, logistic model trees, and C4.5 decision trees and is complemented by an evolutionary feature selection for selecting the most beneficial feature subsets leading to the best quality gain. In contrast to other research, this study uses a comparatively large set of 400 GPS trajectories which have been recorded in rural and urban European areas. Results contribute to a higher reliability as well as a broader applicability of GPS-only travel mode detection.
Richard Brunauer; Michael Hufnagl; Karl Rehrl; Andreas Wagner; Aaron Wagner. Motion pattern analysis enabling accurate travel mode detection from GPS data only. 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) 2013, 404 -411.
AMA StyleRichard Brunauer, Michael Hufnagl, Karl Rehrl, Andreas Wagner, Aaron Wagner. Motion pattern analysis enabling accurate travel mode detection from GPS data only. 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013). 2013; ():404-411.
Chicago/Turabian StyleRichard Brunauer; Michael Hufnagl; Karl Rehrl; Andreas Wagner; Aaron Wagner. 2013. "Motion pattern analysis enabling accurate travel mode detection from GPS data only." 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) , no. : 404-411.